List of Training Materials
identifier | Additional keywords | Author(s) | Format | Prerequisites | Topics covered | Event | |
---|---|---|---|---|---|---|---|
Microscopie image analysis on Bio Image Archive |
1687 | Workshop material | This course is aimed at scientists working with bioimage data across the life sciences. It is suitable for those involved in creating bioimages or taking their first steps in analysis. The content would also be suitable for those wanting to learn more about the BioImage Archive and gain experience with machine learning approaches for image analysis. The programme will be of particular interest to bio-image analysts with questions relating to the use of ‘big data’ and using the wealth of publically available data curated in the BioImageArchive. The course should be accessible to members of the bioimaging community and does not require prior experience with machine learning methods or use of the BioImage Archive is necessary, but applicants are encouraged to explore the resources below before starting their application. Applicants should be comfortable with basic programming tasks and have experience working with Python. Prerequisite reading:
|
Data handling, Cell segmentation, Machine learning, Image analysis | |||
Lecture Bio-image analysis, biostatistics, programming and machine learning for computational biology at the Biotechnology Center, TU Dresden, 2021 |
1677 | Programming | Robert Haase, DFG Cluster of Excellence, "Physics of Life", TU Dresden | Workshop material | Image classification | ||
Lecture Applied Bio-image Analysis at Biotechnology Center, TU Dresden, 2020 |
1676 | Robert Haase, DFG Cluster of Excellence, "Physics of Life", TU Dresden | video tutorial | Image convolution | |||
Customizing ImageJ |
1675 | Robert Haase, DFG Cluster of Excellence, "Physics of Life", TU Dresden | Workshop material | ImageJ Macros | Max Planck BioImaging Core Unit Network - Advanced ImageJ Macro Course, 2021 | ||
Sharing and licensing material |
1674 | licensing | Robert Haase, DFG Cluster of Excellence, "Physics of Life", TU Dresden | Workshop material | Data sharing | EMBO Practical Course on Advanced Methods in Bioimage Analysis 2021 | |
On-the-fly image processing with Python and napari |
1673 | Robert Haase, DFG Cluster of Excellence, "Physics of Life", TU Dresden | Workshop material | Interactive segmentation | Smart Microscopy Workshop at the Center for Cellular imaging at the University … | ||
Image processing with Python |
1669 | Tutorial | This lesson assumes you have a working knowledge of Python and some previous exposure to the Bash shell. |
Image processing | |||
Image Analysis Training Resources |
1668 | Jan Eglinger, Stephan Hellfrish, Aliaksandr Halavatyi, Christian Tischer, Toby Hodges, Antonio Politi | Tutorial | None if staring from first module, otherwise prerequisites are indicated for each module. |
Image segmentation, Image processing, Image convolution | ||
Data Science in Cell Imaging (DSCI) course material |
1654 | High content single cell phenotypic profiling, Deep learning in microscopy, Public data repositories, data harmonization, integration and fusion, Data-modeling of live cell imaging | Assaf Zaritsky | No prior biological knowledge is required; all background will be covered in the lectures. Some background in mathematics and programming is required. Prior knowledge in machine learning and/or computer vision is highly recommended, but not necessary. |
Bioimage informatics, Machine learning | ||
Bioimage analysis with Icy |
1643 | protocols, Icy, automation, reproducibility | Marion Louveaux | video tutorial | Basic image analysis concepts. Target audience Early Careers: Ideally suited. Learn how to make reproducible automated bioimage analysis workflows even without programming knowledge Bioimage Analysts / Facility Staff: Very useful for teaching purposes and if you need to quickly deliver modifiable, reusable workflows to non-programming user
|
Recording of the webinar | |
Introduction to R for bioimage analysis |
1581 | Marion Louveaux | NEUBIAS TS10 (Luxembourg) | ||||
Deep Learning from scratch |
1580 | RASTI Pejman , ROUSSEAU David | video tutorial | Coding notions |
Machine learning, Classification | ||
Spatiotemporal quantification of monolayer cell migration |
1554 | Zaritsky Assaf | Tutorial | Bio image analysts |
Collective object tracking | /neubias-ts7-0 | |
Analysis of filopodia dynamics |
1552 | Urbancic Vasja, Butler Richard | Tutorial | Bio image analysts |
Filament tracing, Isolated object tracking | /neubias-ts7-0 | |
High Content Image data Screening and Analysis |
1551 | Molnar Csaba | Tutorial | bio image analysts |
High content screening | /neubias-ts7-0 | |
Stitch Tiles, Flat Field Correction, Quantify ProtX intensity at Nuclei |
1550 | Tutorial | Early Carreer Investigators without previous experience with image analysis or ImageJ |
Montage | /neubias-ts5 | ||
Introduction to ImageJ macros: Quantify the enrichment of NPC proteins at the nuclear envelope, relative to its cytoplasmic localisation |
1549 | Cordelieres Fabrice P | Tutorial | Early Carreer Investigators without previous experience with image analysis or ImageJ |
/neubias-ts5 | ||
Working with objects: measurements in 2D and 3D |
1548 | Cordelieres Fabrice P. | Tutorial | Early Carreer Investigators without previous experience with image analysis or ImageJ |
Spot detection, Object counting, Object detection | /neubias-ts2 | |
Analysis of Microtubule Orientation: Tracking with ImageJ, Directionality Analysis with Matlab |
1547 | Miura Kota, Pengo Thomas, Noerrelykke Simon | Tutorial | Must understand basics of Matlab as in the Training Material "Introduction to Matlab" |
Particle tracking | /neubias-ts1 | |
Visualization of 3D images with Matlab |
1546 | Cardone Giovanni | Tutorial | Must understand basics of Matlab as in the TM "Introduction to Matlab" |
Visualisation | /neubias-ts1 | |
2D image processing and Data analysis with Matlab |
1545 | de Castro Aguiar Paulo, Cardone Giovanni, Lindblad Joakim | Tutorial | Must understand basics of Matlab as in the TM "Introduction to Matlab" |
Image segmentation | /neubias-ts1 | |
Introduction to Matlab |
1544 | de Castro Aguiar Paulo, Cardone Giovanni, Lindblad Joakim | Tutorial | Matlab, for Beginners |
/neubias-ts1 | ||
From workflows to simple batch macros: Quantify intensity at the nuclear envelope. |
1543 | Klemm Anna | Early Carreer Investigators without previous experience with image analysis or ImageJ |
/neubias-ts2 | |||
From workflows to simple batch macros: Measure Phalloidin in the nucleus area. |
1542 | Martins Nuno | Tutorial | Early Carreer Investigators without previous experience with image analysis or ImageJ |
/neubias-ts2 | ||
Recording simple macros for batch processing v2 |
1541 | Klemm Anna | Tutorial | Early Carreer Investigators without previous experience with image analysis or ImageJ |
Image visualisation | /neubias-ts4 | |
Recording simple macros for batch processing |
1540 | Martins Nuno | Tutorial | Early Carreer Investigators without previous experience with image analysis or ImageJ |
Image visualisation | /neubias-ts2 | |
Batch ImageJ macro |
1539 | Helfrich Stefan | Tutorial | Montage | /neubias-ts5 | ||
Tumor Blood Vessels: 3D Tubular Network Analysis |
1538 | Tisher Christian, Tosi Sebastien | Tutorial | ImageJ Macros |
Filament tracing, Visualisation, Fluorescence microscopy, Light-sheet microscopy | /neubias-ts1 | |
Macro Programming in ImageJ |
1537 | Miura Kota | Book Chapter, Tutorial | ||||
Hands-on exercises for learning Imaris |
1536 | Golani Ofra, Reinat Nevo | Spot detection, Visualisation, Particle tracking, Plotting, Surface rendering | ||||
Building a workflow with CellProfiler |
1535 | Wahlby Carolina | Tutorial | None |
Cell segmentation, Cell tracking, Spot detection | /neubias-ts2 | |
KNIME Workflow |
1534 | Horn Martin | /neubias-ts3 | ||||
ICY Protocols and Scripts |
1533 | Dufour Axexandre | /neubias-ts3 | ||||
Introduction to ImarisXT using MATLAB |
1532 | Beati Igor | Tutorial | Bio Image Analysts |
Spot detection | /neubias-ts3 | |
ImageJ2 Ops Scripting |
1531 | Rueden Curtis | Tutorial | Bio Image Analysts |
/neubias-ts3 | ||
Developing for ImageJ and Friends |
1530 | Tinevez Jean-Yves | Bio Image Analysts |
/neubias-ts3 | |||
Big Data & 3D Visualization |
1529 | Jug Florian, Pietzsch Tobias | Visualisation, Data handling | /neubias-ts7-0 | |||
Deconstructing co-localisation workflows: from co-expression assessment to super-resolved co-distribution analysis |
1528 | Cordelières Fabrice P. | Bio Image Analysts |
Colocalisation analysis, Object-based colocalisation, Pixel-based colocalisation | /neubias-ts7-0 | ||
Using machine learning to perform image quality control |
1526 | Beth Cimini | Machine learning | ||||
CellProfiler Tutorial: pixel-based classification |
1525 | Karhohs Kyle | Tutorial | no need for programmation |
Cell segmentation, Machine learning | ||
Introduction to Image Segmentation |
1524 | Arganda-Carreras Ignacio | Tutorial | Cell segmentation, Morphological operation | /neubias-ts5 | ||
Introduction to ImageJ: basic operations |
1523 | Martins Nuno P. | /neubias-ts4 | ||||
Restoration of BioImage by Digital Filters |
1522 | Tosi Sébastien | Image processing | /neubias-ts3 | |||
SR-Tesseler Hands-On |
1521 | Levet Florian | Tutorial | Bio Image Analyst |
Super-resolution microscopy | /neubias-ts3 | |
Working with pixels: filters, morphomaths and binary operations |
1520 | Aguiar Paulo | Tutorial | must understand basic operations in imageJ |
Morphological operation | /neubias-ts2 | |
NEUBIAS TS11 |
1519 | ||||||
NEUBIAS TS10 |
1518 | ||||||
NEUBIAS TS9 |
1517 | ||||||
NEUBIAS TS8 |
1516 | ||||||
NEUBIAS TS7 |
1515 | ||||||
NEUBIAS TS6 |
1513 | ||||||
Neubias TS5 |
1512 | ||||||
NEUBIAS TS4 |
1511 | ||||||
NEUBIAS TS3 |
1510 | ||||||
NEUBIAS TS2 |
1509 | ||||||
Assembling data for publication using FigureJ |
1508 | Cordelières Fabrice P. | Tutorial | must understand basic operations in imageJ |
Image visualisation | ||
Working with stacks: 3D image visualisation |
1507 | Cordelières Fabrice P. | Tutorial | must understand basic operations in imageJ |
Visualisation | ||
From pixels to microns |
1506 | Sampaio Paula | Tutorial | must understand basic operations in imageJ |
Image analysis | ||
Working with color images and images in color |
1505 | Sampaio Paula | Tutorial | must understand basic operations in imageJ |
Image processing | /neubias-ts2 | |
Checking and preserving the quantitative intensity content of your images |
1504 | Tisher Christian | Tutorial | Early Carreer Investigators without previous experience with image analysis or ImageJ |
Contrast enhancement, Conversion | /neubias-ts2 | |
Introduction to ImageJ basic operations |
1503 | Paul-Gilloteaux Perrine | Tutorial | Bioimage informatics | /neubias-ts2 | ||
EB1 tracking with Matlab |
1502 | Cardone Giovanni, de Castro Paulo, Lindblad Joakim | Tutorial | Object tracking, Particle tracking | |||
EB1 tracking with IJ |
1501 | Miura Kota, Cardone Giovanni | Tutorial | Object tracking, Particle tracking | |||
Batch_Filter_CaseStudy part 2 |
1499 | Tosi Sébastien | Tutorial | must know basics of ImageJ/FIJI |
Image processing | Event | |
Batch_Filter_CaseStudy part1 |
1498 | Guiet Romain, Tosi Sébastien | Tutorial | must know basics of ImageJ/FIJI |
Image processing | /neubias-ts1 | |
Batch_Filter_CaseStudy part3 Stitch Tiles, Flat Field Correction, Quantify ProtX intensity at Nuclei |
1500 | Guiet Romain | must know basics of ImageJ/FIJI |
/neubias-ts1 | |||
Introduction to Bio Image analysis |
1497 | Kota Miura | Tutorial | none |
Bioimage informatics, Image analysis | ||
Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development |
1494 | Jaroslav Icha, Christopher Schmied, Jaydeep Sidhaye, Pavel Tomancak, Stephan Preibisch, Caren Norden | |||||
3D object based colocalisation |
1451 | Fabrice Cordelières, Chong Zhang | ImageJ macro knowledge |
Colocalisation analysis, Object-based colocalisation | /neubias-ts1 | ||
Image Processing and Analysis for Life Scientists MOOC |
1446 | Arne Seitz, Romain Guiet, Olivier Burri from BIOP EPFL | none. |
Image analysis, Image processing, Light microscopy, High content screening | |||
video tutorial on 3D vessel segmentation of synchrotron phase contrast tomography |
1420 | synchrotron | Tom de Vries, Chong Zhang | video tutorial | Image segmentation, Phase contrast microscopy, Contrast enhancement, Watershed segmentation | ||
ImageJ1 - ImageJ2 transition cheat sheet |
1373 | Robert Haase, Kouichi C. Nakamura, Jan Eglinger, ImageJ community | |||||
Simultaneous ImageJ script and plugin development |
1372 | Robert Haase | Tutorial | ||||
NEUBIAS TS1 |
1365 | ||||||
Introduction to ImageJ macro language |
1366 | Fabrice Cordeliéres, Ofra Golani | Tutorial, Workshop material | must know basics of ImageJ/FIJI |
ImageJ Macros | NEUBIAS TS1 Facility Staff School - Barcelona 2016 | |
Kota Miura (ed) "Bioimage Data Analysis", Textbook, Wiley |
45 | ||||||
Rafael C. Gonzalez, Richard E. Woods."Digital Image Processing", Pearson, 2008 |
70 | ||||||
Understanding the fundamental mechanisms of biofilms development and dispersal: BIAM (Biofilm Intensity and Architecture Measurement), a new tool for studying biofilms as a function of their architecture and fluorescence intensity |
55 | ||||||
Quantitative Evaluation of Multicellular Movements in Drosophila Embryo |
6 |